1. Field of Invention
The present disclosure relates to stray-light correction in imaging instruments and, more particularly, to stray-light correction using a stray-light correction matrix derived from point spread functions (PSFs) characterized from imaging instruments.
2. Description of Related Art
Radiometric/photometric data may be acquired using imaging instruments, such as digital cameras, hyperspectral imaging systems, imaging radiometers, imaging photometers and other types of imaging instruments or optical systems. Image quality, including image sharpness, contrast, and stray light, is often an important characteristic of such imaging instruments or optical systems.
The quality of images for such imaging instruments can be improved through state of the art hardware designs and advanced manufacturing processes. This hardware approach, however, may be limited by physics and available technologies. For example, detector window reflections, minimum achievable surface reflections and/or scattering from lenses, mirrors, and other types of optical components. This hardware approach may also be limited by the manufacturing cost of imaging instruments.
Stray light in an imaging instrument may be the dominant source of measurement errors. For example, for a photometer/radiometer, stray light may be the dominant source of measurement error involving the contrast ratio of flat panel displays. Stray-light errors in an imaging instrument are often known as “veiling glare” in photometry and “size-of-source effect” in radiometry.
There is a need for an image improvement technique that can significantly reduce measurement errors, while taking into account errors due to stray light.
Various mathematical theories and algorithms have been devised and implemented in order to improve the quality of images for imaging instruments or optical systems. These previously developed techniques are generally based on the deconvolution algorithms to improve image sharpness, while failing to focus on stray light errors. These techniques incorporate the use of complex mathematical theories. When a computer is required to perform complex mathematics, the computer's processor may be heavily burdened, thus resulting in slow response time. Thus, using these techniques involving complex mathematical theories, it may it may not be possible to perform fast corrections of stray-light errors. Moreover, such techniques may require a significant amount of processing power. Again, this technique does not focus on measurement errors due to stray light.
Accordingly, there is further a need for an image improvement technique that does not require complicated mathematical theories, and which can perform robust, fast correction of stray-light errors.